Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks
Tactile sensory systems play a vital role in various emerging fields including robotics, prosthetics, and human–machine interfaces. However, traditional tactile sensors are typically designed to detect a single stimulus through a lock‐and‐key mechanism, which poses substantial challenges in the real...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-04-01
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| Series: | Advanced Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aisy.202300631 |
| _version_ | 1797197611851055104 |
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| author | Junho Lee Jee Young Kwak Kyobin Keum Kang Sik Kim Insoo Kim Myung‐Jae Lee Yong‐Hoon Kim Sung Kyu Park |
| author_facet | Junho Lee Jee Young Kwak Kyobin Keum Kang Sik Kim Insoo Kim Myung‐Jae Lee Yong‐Hoon Kim Sung Kyu Park |
| author_sort | Junho Lee |
| collection | DOAJ |
| description | Tactile sensory systems play a vital role in various emerging fields including robotics, prosthetics, and human–machine interfaces. However, traditional tactile sensors are typically designed to detect a single stimulus through a lock‐and‐key mechanism, which poses substantial challenges in the realization of multimodal tactile sensors. To address this issue, the convergence of tactile sensory systems with artificial neural network and machine learning (ML) platforms has been utilized to enhance the capabilities of multimodal sensors and enable signal decoupling/interpretation of mixed tactile stimuli. Herein, recent progress in multimodal sensors that can simultaneously identify various stimuli such as strain, pressure, and temperature is reviewed, providing in‐depth understanding of materials, structures, and methodologies. In addition, accurate interpretation of signals from mixed tactile stimuli under complex conditions remains challenging. This review presents a comprehensive exploration of ML algorithms that mimic human neural networks, discussing their significance in advancing smart sensory systems and improving signal interpretation in complex and dynamic environments. |
| first_indexed | 2024-04-24T06:46:43Z |
| format | Article |
| id | doaj.art-8bae7bceebf94956bcbbf2b9dd322bb0 |
| institution | Directory Open Access Journal |
| issn | 2640-4567 |
| language | English |
| last_indexed | 2024-04-24T06:46:43Z |
| publishDate | 2024-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Intelligent Systems |
| spelling | doaj.art-8bae7bceebf94956bcbbf2b9dd322bb02024-04-22T18:07:16ZengWileyAdvanced Intelligent Systems2640-45672024-04-0164n/an/a10.1002/aisy.202300631Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural NetworksJunho Lee0Jee Young Kwak1Kyobin Keum2Kang Sik Kim3Insoo Kim4Myung‐Jae Lee5Yong‐Hoon Kim6Sung Kyu Park7Displays and Devices Research Lab Department of Intelligent Semiconductor Engineering Chung‐Ang University Seoul 06974 Republic of KoreaDisplays and Devices Research Lab Department of Intelligent Semiconductor Engineering Chung‐Ang University Seoul 06974 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaDisplays and Devices Research Lab Department of Intelligent Semiconductor Engineering Chung‐Ang University Seoul 06974 Republic of KoreaDepartment of Medicine University of Connecticut School of Medicine Farmington CT 06030 USAConvergence Research Institute Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaDisplays and Devices Research Lab Department of Intelligent Semiconductor Engineering Chung‐Ang University Seoul 06974 Republic of KoreaTactile sensory systems play a vital role in various emerging fields including robotics, prosthetics, and human–machine interfaces. However, traditional tactile sensors are typically designed to detect a single stimulus through a lock‐and‐key mechanism, which poses substantial challenges in the realization of multimodal tactile sensors. To address this issue, the convergence of tactile sensory systems with artificial neural network and machine learning (ML) platforms has been utilized to enhance the capabilities of multimodal sensors and enable signal decoupling/interpretation of mixed tactile stimuli. Herein, recent progress in multimodal sensors that can simultaneously identify various stimuli such as strain, pressure, and temperature is reviewed, providing in‐depth understanding of materials, structures, and methodologies. In addition, accurate interpretation of signals from mixed tactile stimuli under complex conditions remains challenging. This review presents a comprehensive exploration of ML algorithms that mimic human neural networks, discussing their significance in advancing smart sensory systems and improving signal interpretation in complex and dynamic environments.https://doi.org/10.1002/aisy.202300631machine learningneural networkssmart sensorstretchable sensortactile sensors |
| spellingShingle | Junho Lee Jee Young Kwak Kyobin Keum Kang Sik Kim Insoo Kim Myung‐Jae Lee Yong‐Hoon Kim Sung Kyu Park Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks Advanced Intelligent Systems machine learning neural networks smart sensor stretchable sensor tactile sensors |
| title | Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks |
| title_full | Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks |
| title_fullStr | Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks |
| title_full_unstemmed | Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks |
| title_short | Recent Advances in Smart Tactile Sensory Systems with Brain‐Inspired Neural Networks |
| title_sort | recent advances in smart tactile sensory systems with brain inspired neural networks |
| topic | machine learning neural networks smart sensor stretchable sensor tactile sensors |
| url | https://doi.org/10.1002/aisy.202300631 |
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